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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2401.05653 |
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Table of Contents:
- This paper explores the application of Shapley Value Regression in dissecting marketing performance at channel-partner level, complementing channel-level Marketing Mix Modeling (MMM). Utilizing real-world data from the financial services industry, we demonstrate the practicality of Shapley Value Regression in evaluating individual partner contributions. Although structured in-field testing along with cooperative game theory is most accurate, it can often be highly complex and expensive to conduct. Shapley Value Regression is thus a more feasible approach to disentangle the influence of each marketing partner within a marketing channel. We also propose a simple method to derive adjusted coefficients of Shapley Value Regression and compare it with alternative approaches.